AN ultrasound imaging study of the tense-lax distinction in canadian french vowels
Bibliographic record
Abstract
Advanced tongue root (ATR) vowels are produced with significant tongue root advancement, creating a large pharyngeal resonant cavity that is not present during production of non-advanced vowels.Acoustically, this results in a lowered first formant (F1) for ATR vowels as compared to non-ATR vowels.This difference is most prominent among high vowels (Ladefoged and Maddieson, 1996).In terms of phonological features, advanced and non advanced tongue root correspond to [+ATR] and [-ATR], respectively.These features are correlated with traditionally labelled 'tense' and 'lax' vowels in Germanic languages.Cross-linguistically, a number of gestural strategies are employed to create a distinction among so-called tense and lax vowels.In Igbo, these vowels differ only in tongue root position, while in Akan and Germanic languages such as English, they differ in both tongue root position and tongue body height (Ladefoged and Maddieson, 1996).A third possible method of contrasting tense and lax vowels is by varying tongue body height alone.With respect to Canadian French (CF), there has been no articulatory evidence to support the hypothesis that tense and lax vowels are distinguished in a way similar to Igbo on the one hand, or Akan, English and German on the other.Acoustic evidence (Sguin, 2010) shows that tense high vowels in CF have a lower F1 than their lax counterparts.However, as mentioned above, a decrease in F1 could be caused by a number of lingual gestures, of which tongue root advancement is one possibility.Nonetheless, a prevalent assumption in literature that treats with the phonetic and phonological properties of tense and lax high vowels in Canadian French, especially with respect to harmony (Poliquin, 2006), is that these vowels are distinguished by tongue root position.More specifically, tense high vowels (/i y u/) are assumed to be articulated with
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".